2025
Bachelor Theses
1.
Delarue, Simon
Learning on graphs : from algorithms to socio-technical analyses on AI Bachelor Thesis
Telecom Paris, 2025, (HAL Id: tel-04963643).
@bachelorthesis{Delarue2025,
title = {Learning on graphs : from algorithms to socio-technical analyses on AI},
author = {Simon Delarue},
url = {https://theses.hal.science/tel-04963643v1/file/142478_DELARUE_2025_archivage.pdf
https://theses.hal.science/tel-04963643v1},
year = {2025},
date = {2025-02-24},
school = {Telecom Paris},
abstract = {Artificial Intelligence (AI) techniques and algorithms are now deeply embedded in our daily lives. While they offer promising possibilities, their expanding presence in high- stake decision-making domains such as healthcare, justice, and industry raises significant societal, ethical, environmental, and governance issues. Far from being neutral tools, AI models have transformed our practices by introducing or amplifying biases – such as those related to race or gender – and have led to broader consequences, reshaping debates on issues such as the environmental impact of digitalisation. To address the challenges posed by the rapid expansion of AI technologies, and as these issues begin to be considered within international regulations like the AI Act in Europe, it is essential for scientists and developers to incorporate these considerations into their approaches. This requires moving beyond a restricted focus on performance to include aspects like scalability, simplicity, and explainability. This thesis examines the potential of attributed graph-based approaches to address both the technical challenges posed by AI methods, and the socio-technical questions that arise from their complex relationship with society. The first part of this thesis explores how graph-based methods can meet the require- ments for efficiency, scalability, and simplicity in learning techniques. Graphs, i.e. sets of nodes connected to each other through edges, enable the modelling of complex re- lational data and draw on contributions from fields ranging from computer science to social sciences, offering promising solutions to the limitations encountered in AI. First, through a software contribution, we show how the inherent sparsity of complex networks can be leveraged within model implementation to reduce the computational cost of cur- rent approaches. Then, by examining the capabilities of non-neural attributed graph approaches, this thesis shows that simple methods can outperform state-of-the-art neu- ral networks in capturing the structural complexity of real-world data, thereby providing scalable and generalisable solutions to graph-based machine learning tasks such as node classification and link prediction. Finally, we design an attributed pattern mining ap- proach to derive interesting and easily understandable insights from complex networks. Recognising the need for diverse analytical approaches to understand the complex entanglements among current AI techniques, what we aim to achieve with them, and how they transform our uses, the second part of this thesis shifts to an interdisciplinary exam- ination of AI as a socio-technical system. This part explores how AI can be re-envisioned not only as a tool but also as an object of study. By framing AI as an ecosystem shaped by diverse stakeholders and societal concerns, this thesis uses graph-based models to map the interactions and tensions within AI, particularly around explainability, ethics, and environmental impact. For this purpose, we conduct a user study to examine the po- v tential of attributed graph-based explanations to enhance users’ perception of AI-based recommendations, and reveal the complex link between users’ preference towards expla- nation design and the understanding gain these explanations allow. In a second analysis, we build a corpus of AI charters and manifestos for ethics, which we make publicly avail- able. Using this corpus, we quantitatively analyse the interactions among key actors forming the social world of AI ethics in order to understand their roles in influencing AI governance and regulation. Finally, we explore how AI-related scientists incorporate their environmental concerns into their research using attributed graph analysis. This study reveals that environmental concerns remain largely framed through a technical perspective, with little consideration of the ecological impacts of digitalisation, pointing to the need for a more balanced approach in future research on AI and the environment. Building directly on the work presented in this thesis, we conclude by opening path- ways for future research directions focused on simple and efficient graph-based approaches to learning on complex networks. In a broader context, we also discuss future research avenues that we consider essential, including research rooted in Science and Technology Studies, to assess how digital technologies might evolve as inclusive, responsible, and sustainable tools. },
note = {HAL Id: tel-04963643},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
Artificial Intelligence (AI) techniques and algorithms are now deeply embedded in our daily lives. While they offer promising possibilities, their expanding presence in high- stake decision-making domains such as healthcare, justice, and industry raises significant societal, ethical, environmental, and governance issues. Far from being neutral tools, AI models have transformed our practices by introducing or amplifying biases – such as those related to race or gender – and have led to broader consequences, reshaping debates on issues such as the environmental impact of digitalisation. To address the challenges posed by the rapid expansion of AI technologies, and as these issues begin to be considered within international regulations like the AI Act in Europe, it is essential for scientists and developers to incorporate these considerations into their approaches. This requires moving beyond a restricted focus on performance to include aspects like scalability, simplicity, and explainability. This thesis examines the potential of attributed graph-based approaches to address both the technical challenges posed by AI methods, and the socio-technical questions that arise from their complex relationship with society. The first part of this thesis explores how graph-based methods can meet the require- ments for efficiency, scalability, and simplicity in learning techniques. Graphs, i.e. sets of nodes connected to each other through edges, enable the modelling of complex re- lational data and draw on contributions from fields ranging from computer science to social sciences, offering promising solutions to the limitations encountered in AI. First, through a software contribution, we show how the inherent sparsity of complex networks can be leveraged within model implementation to reduce the computational cost of cur- rent approaches. Then, by examining the capabilities of non-neural attributed graph approaches, this thesis shows that simple methods can outperform state-of-the-art neu- ral networks in capturing the structural complexity of real-world data, thereby providing scalable and generalisable solutions to graph-based machine learning tasks such as node classification and link prediction. Finally, we design an attributed pattern mining ap- proach to derive interesting and easily understandable insights from complex networks. Recognising the need for diverse analytical approaches to understand the complex entanglements among current AI techniques, what we aim to achieve with them, and how they transform our uses, the second part of this thesis shifts to an interdisciplinary exam- ination of AI as a socio-technical system. This part explores how AI can be re-envisioned not only as a tool but also as an object of study. By framing AI as an ecosystem shaped by diverse stakeholders and societal concerns, this thesis uses graph-based models to map the interactions and tensions within AI, particularly around explainability, ethics, and environmental impact. For this purpose, we conduct a user study to examine the po- v tential of attributed graph-based explanations to enhance users’ perception of AI-based recommendations, and reveal the complex link between users’ preference towards expla- nation design and the understanding gain these explanations allow. In a second analysis, we build a corpus of AI charters and manifestos for ethics, which we make publicly avail- able. Using this corpus, we quantitatively analyse the interactions among key actors forming the social world of AI ethics in order to understand their roles in influencing AI governance and regulation. Finally, we explore how AI-related scientists incorporate their environmental concerns into their research using attributed graph analysis. This study reveals that environmental concerns remain largely framed through a technical perspective, with little consideration of the ecological impacts of digitalisation, pointing to the need for a more balanced approach in future research on AI and the environment. Building directly on the work presented in this thesis, we conclude by opening path- ways for future research directions focused on simple and efficient graph-based approaches to learning on complex networks. In a broader context, we also discuss future research avenues that we consider essential, including research rooted in Science and Technology Studies, to assess how digital technologies might evolve as inclusive, responsible, and sustainable tools.
Proceedings
2.
Kim, Haesol; Kim, Eunjae; Jang, Sou Hyun; Shin, Eun Kyong
Semantic Landscape of Legal Lexicons: Unpacking Medical Decision-Making Controversies Proceedings
Springer, vol. 1, 2025, ISSN: 2367-3370, (International Conference on Inventive Computation Technologies http://www.icicts.com).
@proceedings{Kim2025,
title = {Semantic Landscape of Legal Lexicons: Unpacking Medical Decision-Making Controversies},
author = {Haesol Kim and Eunjae Kim and Sou Hyun Jang and Eun Kyong Shin},
url = {https://www.researchgate.net/profile/Jean-Claude-Munyaka-Baraka-2/publication/396901330_Sentiment_Analysis_on_the_Young_People\'s_Perception_About_the_Mobile_Internet_Costs_in_Senegal/links/68fcf9ff220a341aa1583188/Sentiment-Analysis-on-the-Young-Peoples-Perception-About-the-Mobile-Internet-Costs-in-Senegal.pdf#page=144},
doi = {10.1007/978-981-96-9709-0},
issn = {2367-3370},
year = {2025},
date = {2025-12-31},
urldate = {2025-12-31},
booktitle = {Proceedings of Tenth International Congress on Information and Communication Technology},
journal = {ICICT 2025},
volume = {1},
publisher = {Springer},
abstract = {This study empirically examined historical trajectories of the semantic landscape of legal conflicts over medical decision-making. We unveiled the lexical structures of lawsuit verdicts, tracing how the core concepts of shared decision-making (SDM)-duty of care, duty to explain, self-determination-have developed and been contextualized in legal discourses. We retrieved publicly available court verdicts using the search keyword ‘patient’ and screened them for relevance to doctor-patient communications. The final corpus comprised 251 South Korean verdicts issued between 1974 and 2023. We analyzed the verdicts using neural topic modeling and semantic network analysis. Our study showed that topic diversity has expanded over time, indicating increased complexity of semantic structures regarding medical decision-making conflicts. We also found two dominant topics: disputes over healthcare providers’ liability and disputes over the compensation for medical malpractice.
The results of semantic network analysis showed that the rhetorics of patients’ right to medical self-determination are not closely tied to the professional responsibility to explain and care. The decoupled semantic relationships of patients’ right and health professionals’ duties revealed the barriers of SDM implementations.},
note = {International Conference on Inventive Computation Technologies
http://www.icicts.com},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
This study empirically examined historical trajectories of the semantic landscape of legal conflicts over medical decision-making. We unveiled the lexical structures of lawsuit verdicts, tracing how the core concepts of shared decision-making (SDM)-duty of care, duty to explain, self-determination-have developed and been contextualized in legal discourses. We retrieved publicly available court verdicts using the search keyword ‘patient’ and screened them for relevance to doctor-patient communications. The final corpus comprised 251 South Korean verdicts issued between 1974 and 2023. We analyzed the verdicts using neural topic modeling and semantic network analysis. Our study showed that topic diversity has expanded over time, indicating increased complexity of semantic structures regarding medical decision-making conflicts. We also found two dominant topics: disputes over healthcare providers’ liability and disputes over the compensation for medical malpractice.
The results of semantic network analysis showed that the rhetorics of patients’ right to medical self-determination are not closely tied to the professional responsibility to explain and care. The decoupled semantic relationships of patients’ right and health professionals’ duties revealed the barriers of SDM implementations.
The results of semantic network analysis showed that the rhetorics of patients’ right to medical self-determination are not closely tied to the professional responsibility to explain and care. The decoupled semantic relationships of patients’ right and health professionals’ duties revealed the barriers of SDM implementations.
2023
Conferences
3.
van der Wouden, Puck; van der Heijden, Geert; Shemesh, Hagay; van den Besselaar, Peter
Does research intensity reflect dental care demand? Conference
27th International Conference on Science, Technology and Innovation Indicators (STI 2023) 2023.
@conference{nokey,
title = {Does research intensity reflect dental care demand?},
author = {Puck van der Wouden and Geert van der Heijden and Hagay Shemesh and Peter van den Besselaar},
url = {https://dapp.orvium.io/deposits/6443b9ce034d53c59822ef3b/view},
doi = {https://doi.org/10.55835/6443b9ce034d53c59822ef3b},
year = {2023},
date = {2023-04-22},
organization = {27th International Conference on Science, Technology and Innovation Indicators (STI 2023)},
abstract = {In this paper we address the question whether (i) the Dutch dental research portfolio reflects the dental care demand, and whether (ii) the results of this research does reach the dental care professionals. In order to answer these questions, we analyzed the content of the Dutch Journal of Dentistry (NTvT), a Dutch language professional journal which explicitly aims at disseminating useful knowledge to dental professionals. The research topics addressed in the journal were compared with (i) dental publications written by authors with a Dutch affiliation in international journals and with (ii) expenditures in the various types of oral healthcare. The analysis shows topical change over time, with more emphasis in NTvT on topics as social dentistry, and less attention for basic science topics. At the same time, the Dutch dental research portfolio (reflected by publications in international journals) does not reflect that trend. In addition, it appears that the largest domains of care with the highest share of oral healthcare expenditures (e.g. cariology and prevention) have the lowest attention in research. This applies to both international publications, as to the research disseminated through the professional journal NTvT.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
In this paper we address the question whether (i) the Dutch dental research portfolio reflects the dental care demand, and whether (ii) the results of this research does reach the dental care professionals. In order to answer these questions, we analyzed the content of the Dutch Journal of Dentistry (NTvT), a Dutch language professional journal which explicitly aims at disseminating useful knowledge to dental professionals. The research topics addressed in the journal were compared with (i) dental publications written by authors with a Dutch affiliation in international journals and with (ii) expenditures in the various types of oral healthcare. The analysis shows topical change over time, with more emphasis in NTvT on topics as social dentistry, and less attention for basic science topics. At the same time, the Dutch dental research portfolio (reflected by publications in international journals) does not reflect that trend. In addition, it appears that the largest domains of care with the highest share of oral healthcare expenditures (e.g. cariology and prevention) have the lowest attention in research. This applies to both international publications, as to the research disseminated through the professional journal NTvT.
2022
Journal Articles
4.
Rikap, Cecilia
The expansionary strategies of intellectual monopolies: Google and the digitalization of healthcare Journal Article
In: Economy and Society, 2022.
@article{Rikap2022b,
title = {The expansionary strategies of intellectual monopolies: Google and the digitalization of healthcare},
author = {Cecilia Rikap},
url = {https://www.tandfonline.com/doi/full/10.1080/03085147.2022.2131271
https://www.tandfonline.com/doi/epdf/10.1080/03085147.2022.2131271?needAccess=true&role=button},
doi = {https://doi.org/10.1080/03085147.2022.2131271},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
journal = {Economy and Society},
abstract = {As big tech companies are entering new industrial sectors, an open question concerns the drivers of their expansionary strategies. This paper proposes that these companies are currently entering sectors based on their data-driven intellectual monopoly power, thereby complementing the preliminary answer provided by political economy research which has argued that expansion is driven by their infrastructural power. This approach is developed through a historical analysis of tech giants as companies that systematically turn knowledge and data into intangible assets, showing their expansionary strategies in the healthcare sector to be mainly driven by insights obtained from those intangible assets (a monopolized intangibles driver) and by a quest for conquering new knowledge and data to perpetuate their intellectual monopolies (an intangibles prospecting driver). The paper further illustrates its arguments through a case study of Google’s expansionary strategy and its prioritized incursion into healthcare.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As big tech companies are entering new industrial sectors, an open question concerns the drivers of their expansionary strategies. This paper proposes that these companies are currently entering sectors based on their data-driven intellectual monopoly power, thereby complementing the preliminary answer provided by political economy research which has argued that expansion is driven by their infrastructural power. This approach is developed through a historical analysis of tech giants as companies that systematically turn knowledge and data into intangible assets, showing their expansionary strategies in the healthcare sector to be mainly driven by insights obtained from those intangible assets (a monopolized intangibles driver) and by a quest for conquering new knowledge and data to perpetuate their intellectual monopolies (an intangibles prospecting driver). The paper further illustrates its arguments through a case study of Google’s expansionary strategy and its prioritized incursion into healthcare.
2021
Journal Articles
5.
Penteado, Bruno Elias; Fornazin, Marcelo; Castro, Leonardo; Freire, Sandro Luis
Mapeando a dinâmica da informática médica: uma análise bibliométrica do campo científico Journal Article
In: Revista Eletrônica de Comunicação, vol. 15, iss. 4, pp. 869-889, 2021, ISSN: 1981-6278.
@article{Penteado2021d,
title = {Mapeando a dinâmica da informática médica: uma análise bibliométrica do campo científico},
author = {Bruno Elias Penteado and Marcelo Fornazin and Leonardo Castro and Sandro Luis Freire},
url = {https://www.reciis.icict.fiocruz.br/index.php/reciis/article/view/2395},
doi = {10.29397/reciis.v15i4.2395},
issn = {1981-6278},
year = {2021},
date = {2021-12-01},
journal = {Revista Eletrônica de Comunicação},
volume = {15},
issue = {4},
pages = {869-889},
abstract = {A saúde digital é um assunto emergente em fóruns acadêmicos, nas políticas públicas e nas organizações de saúde. Supondo que a saúde digital deriva de conhecimentos da informática médica, este artigo apresenta resultados de uma pesquisa bibliométrica sobre a evolução conceitual e tecnológica do campo da informática médica nas últimas décadas, enfatizando aspectos metodológicos. O trabalho realizou bibliometria em metadados de 100 mil artigos indexados sob a categoria ‘medical informatics’ na base de dados Web of Science entre os anos de 1960 e 2020. Foram realizadas análises longitudinais com utilização dos softwares Bibliometrix e CorText em três eixos: quantidade de publicações, países dos autores e palavras-chave. Conforme a hipótese metodológica que orientou o estudo, as mudanças terminológicas verificadas ao longo do tempo oferecem uma visão aproximativa das mudanças conceituais e tecnológicas do campo de pesquisa da informática médica. Os resultados mostram que esse campo de investigação apresentou crescimento consistente ao longo das últimas seis décadas, expandindo-se para diferentes países. As mudanças terminológicas e conceituais detectadas pela análise de palavras-chave permitiram a identificação de períodos temporais definidos, associados a rótulos genéricos como ‘health informatics’, ‘e-health’. O rótulo ‘medical informatics’ é recorrente como termo mais geral a designar o campo de aplicação, em razão de sua adoção por associações científicas internacionais a partir da década de 1970. Nos últimos cincos anos, pode-se identificar a emergência do termo ‘digital health’, que possivelmente será o conceito dominante na década que se inicia. A análise de palavras-chave também indica a associação entre mudanças terminológicas e de tecnologias, o que reforça as relações entre conceitos e aplicações tecnológicas de cada período.
Digital health is an emerging topic in academic forums, public policies, and healthcare organizations. Assuming that digital health derives from previous medical informatics knowledge, this work presents findings from a bibliometric study on medical informatics technological and conceptual evolution in the last decades, emphasizing methodological aspects. We performed a bibliometric analysis in metadata from 100,000 papers indexed under the category ‘medical informatics’ in the Web of Science database between 1960 and 2020. Longitudinal analysis using software Bibliometrix and CorText were conducted in three axes: frequency of items, authors’ countries, and keywords. Based on the methodological hypothesis guiding the study, the changes in keywords over time offer a proxy view on the conceptual and technological changes in the medical informatics research field. The results show that medical informatics consistently grew over the last six decades, expanding to several countries. Conceptual and technological changes that emerged from the keyword analysis supported the identification of well delimited periods related to general labels, such as: ‘health informatics’ and ‘e-health’. The ‘medical informatics’ is recurring as a general label due to international scientific associations’ adoption since the early 1970s. Moreover, in the last five years, we could identify the term ‘digital health’, which will probably be a major label in the next decade. The keyword analysis also showed the association between labels and technological changes, adding more evidence that these changes are related to concepts and technological applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A saúde digital é um assunto emergente em fóruns acadêmicos, nas políticas públicas e nas organizações de saúde. Supondo que a saúde digital deriva de conhecimentos da informática médica, este artigo apresenta resultados de uma pesquisa bibliométrica sobre a evolução conceitual e tecnológica do campo da informática médica nas últimas décadas, enfatizando aspectos metodológicos. O trabalho realizou bibliometria em metadados de 100 mil artigos indexados sob a categoria ‘medical informatics’ na base de dados Web of Science entre os anos de 1960 e 2020. Foram realizadas análises longitudinais com utilização dos softwares Bibliometrix e CorText em três eixos: quantidade de publicações, países dos autores e palavras-chave. Conforme a hipótese metodológica que orientou o estudo, as mudanças terminológicas verificadas ao longo do tempo oferecem uma visão aproximativa das mudanças conceituais e tecnológicas do campo de pesquisa da informática médica. Os resultados mostram que esse campo de investigação apresentou crescimento consistente ao longo das últimas seis décadas, expandindo-se para diferentes países. As mudanças terminológicas e conceituais detectadas pela análise de palavras-chave permitiram a identificação de períodos temporais definidos, associados a rótulos genéricos como ‘health informatics’, ‘e-health’. O rótulo ‘medical informatics’ é recorrente como termo mais geral a designar o campo de aplicação, em razão de sua adoção por associações científicas internacionais a partir da década de 1970. Nos últimos cincos anos, pode-se identificar a emergência do termo ‘digital health’, que possivelmente será o conceito dominante na década que se inicia. A análise de palavras-chave também indica a associação entre mudanças terminológicas e de tecnologias, o que reforça as relações entre conceitos e aplicações tecnológicas de cada período.
Digital health is an emerging topic in academic forums, public policies, and healthcare organizations. Assuming that digital health derives from previous medical informatics knowledge, this work presents findings from a bibliometric study on medical informatics technological and conceptual evolution in the last decades, emphasizing methodological aspects. We performed a bibliometric analysis in metadata from 100,000 papers indexed under the category ‘medical informatics’ in the Web of Science database between 1960 and 2020. Longitudinal analysis using software Bibliometrix and CorText were conducted in three axes: frequency of items, authors’ countries, and keywords. Based on the methodological hypothesis guiding the study, the changes in keywords over time offer a proxy view on the conceptual and technological changes in the medical informatics research field. The results show that medical informatics consistently grew over the last six decades, expanding to several countries. Conceptual and technological changes that emerged from the keyword analysis supported the identification of well delimited periods related to general labels, such as: ‘health informatics’ and ‘e-health’. The ‘medical informatics’ is recurring as a general label due to international scientific associations’ adoption since the early 1970s. Moreover, in the last five years, we could identify the term ‘digital health’, which will probably be a major label in the next decade. The keyword analysis also showed the association between labels and technological changes, adding more evidence that these changes are related to concepts and technological applications.
Digital health is an emerging topic in academic forums, public policies, and healthcare organizations. Assuming that digital health derives from previous medical informatics knowledge, this work presents findings from a bibliometric study on medical informatics technological and conceptual evolution in the last decades, emphasizing methodological aspects. We performed a bibliometric analysis in metadata from 100,000 papers indexed under the category ‘medical informatics’ in the Web of Science database between 1960 and 2020. Longitudinal analysis using software Bibliometrix and CorText were conducted in three axes: frequency of items, authors’ countries, and keywords. Based on the methodological hypothesis guiding the study, the changes in keywords over time offer a proxy view on the conceptual and technological changes in the medical informatics research field. The results show that medical informatics consistently grew over the last six decades, expanding to several countries. Conceptual and technological changes that emerged from the keyword analysis supported the identification of well delimited periods related to general labels, such as: ‘health informatics’ and ‘e-health’. The ‘medical informatics’ is recurring as a general label due to international scientific associations’ adoption since the early 1970s. Moreover, in the last five years, we could identify the term ‘digital health’, which will probably be a major label in the next decade. The keyword analysis also showed the association between labels and technological changes, adding more evidence that these changes are related to concepts and technological applications.
2020
PhD Theses
6.
Trabelsi, Sonia
Geographies of green and health in Belgium: measurements, opportunities, and challenges PhD Thesis
Université catholique de Louvain, 2020.
@phdthesis{Trabelsi2020,
title = {Geographies of green and health in Belgium: measurements, opportunities, and challenges},
author = {Sonia Trabelsi},
url = {http://hdl.handle.net/2078.1/237672
https://dial.uclouvain.be/pr/boreal/object/boreal%3A237672/datastream/PDF_01/view.pdf},
year = {2020},
date = {2020-02-28},
urldate = {2020-02-28},
school = {Université catholique de Louvain},
abstract = {With an expected increase in urban population and the burden of healthcare costs, the role of the environment for human health has become a topical issue in the scientific and political debate. Numerous studies have investigated the benefits of green spaces on specific morbidities and mortalities while governments are looking to green environments as an alternative to improve citizens' wellbeing and decrease healthcare expenditures. This thesis first explores the definitions and measures of "green" through an analysis of the literature and empirical tests conducted on four landuse data sources in Belgium. It shows that the choice of the measure of green, as well as its level of aggregation, can lead to contradictory conclusions concerning the associations between green and health. Then, using medication reimbursement data recently made available in Belgium, this thesis investigates spatial associations of five groups of medication (a priori associated with the environment) with green spaces. At different scales and at different aggregation levels, medication reimbursement data appear not to be a proxy of individual health but of healthcare practices. Spatial variations of reimbursement are rather linked to exogenous factors such as education of the practitioners, or pharmaceutical and commercial practices. This thesis emphasizes the importance of a clear definition and interpretation of environmental and health data to correctly inform decision makers, particularly when data in use are diverted from their original aim and include spatial information. There is a clear risk of misinterpretation when using new types of data without a multidisciplinary perspective.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
With an expected increase in urban population and the burden of healthcare costs, the role of the environment for human health has become a topical issue in the scientific and political debate. Numerous studies have investigated the benefits of green spaces on specific morbidities and mortalities while governments are looking to green environments as an alternative to improve citizens' wellbeing and decrease healthcare expenditures. This thesis first explores the definitions and measures of "green" through an analysis of the literature and empirical tests conducted on four landuse data sources in Belgium. It shows that the choice of the measure of green, as well as its level of aggregation, can lead to contradictory conclusions concerning the associations between green and health. Then, using medication reimbursement data recently made available in Belgium, this thesis investigates spatial associations of five groups of medication (a priori associated with the environment) with green spaces. At different scales and at different aggregation levels, medication reimbursement data appear not to be a proxy of individual health but of healthcare practices. Spatial variations of reimbursement are rather linked to exogenous factors such as education of the practitioners, or pharmaceutical and commercial practices. This thesis emphasizes the importance of a clear definition and interpretation of environmental and health data to correctly inform decision makers, particularly when data in use are diverted from their original aim and include spatial information. There is a clear risk of misinterpretation when using new types of data without a multidisciplinary perspective.
2019
Masters Theses
7.
Aumüller-Wagner, Sophia; Læarsson, Bartal; Agar, Muhammed; Mituzaite, Kristina; Münz, Janina; Malnača, Linda
Dominant and silent voices in the discourse on Health Smart Homes for the Elderly on Twitter and Scopus Masters Thesis
IT-University of Copenhagen, 2019.
@mastersthesis{Aumüller-Wagner2019,
title = {Dominant and silent voices in the discourse on Health Smart Homes for the Elderly on Twitter and Scopus},
author = {Sophia Aumüller-Wagner and Bartal Læarsson and Muhammed Agar and Kristina Mituzaite and Janina Münz and Linda Malnača},
url = {https://www.dasts.dk/wp-content/uploads/ESPS_Health-smart-home-for-the-elderly.pdf},
year = {2019},
date = {2019-09-01},
school = {IT-University of Copenhagen},
abstract = {Living in a world of demographic change means that aging societies will to a higher extend deal with mobility issues, chronic illnesses, and fall risks. Smart home technologies are increasingly considered in healthcare and could help alleviate the dilemma of people wanting to remain autonomous and independent while growing older. Under the lens of Clarke’s Situational Analysis, this paper explores how health smart homes for the elderly are co-constructed on the platforms of Scopus and Twitter. Using both Big Data and Thick Data, silent voices in the discourse around this technology are uncovered in order to understand how far the innovation of smart homes is aligned with the needs of its users. The main finding of this research paper shows that the field around health smart homes for the elderly is still in its early stages and the needs and concerns of elderly people are not yet considered enough. In order to design smart health homes for the elderly, the researchers propose a requirement pyramid that can aid the design of these future technologies. },
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
Living in a world of demographic change means that aging societies will to a higher extend deal with mobility issues, chronic illnesses, and fall risks. Smart home technologies are increasingly considered in healthcare and could help alleviate the dilemma of people wanting to remain autonomous and independent while growing older. Under the lens of Clarke’s Situational Analysis, this paper explores how health smart homes for the elderly are co-constructed on the platforms of Scopus and Twitter. Using both Big Data and Thick Data, silent voices in the discourse around this technology are uncovered in order to understand how far the innovation of smart homes is aligned with the needs of its users. The main finding of this research paper shows that the field around health smart homes for the elderly is still in its early stages and the needs and concerns of elderly people are not yet considered enough. In order to design smart health homes for the elderly, the researchers propose a requirement pyramid that can aid the design of these future technologies.
LIST OF SCIENTIFIC WORKS THAT HAVE USED CORTEXT MANAGER
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| What types of documents? |
| 254 journal articles |
| 46 Ph.D. thesis |
| 43 conference proceedings |
| 43 conference (not in proceedings) |
| 32 online articles |
| 31 reports |
| 29 bachelorthesis |
| 26 book chapters |
| 22 masters thesis |
| 14 book |
| 13 workshop |
| 5 miscellaneous |
| 4 proceedings |
| 3 presentation |
| 2 workingpaper |
| 1 unpublished |
| 1 manual |
| Main peer-reviewed journals |
|---|
| Main peer-reviewed journals |
| Scientometrics |
| I2D - Information, données & documents |
| Réseaux |
| Revue d’anthropologie des connaissances |
| PloS one |
| Journal of Rural Studies |
| Revue d'anthropologie des connaissances |
| Library Hi Tech |
| Sustainability |
| Energy Economics |
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